Senior Data Engineering Manager

Roles & Responsibility

• Lead mentor and manage a team of data engineers to ensure the successful delivery.
• Oversee the planning, execution, and delivery of data engineering projects.
• Ensure projects are delivered on time, within scope, and within budget, utilizing Agile and SAFe methodologies.
• Design and architect scalable and efficient data systems for Business Intelligence or Data warehouse, including data ingestion, ETL and data integration using Azure Data Bricks, Azure Synapse, Azure Data factory and Azure Devops/GIT.
• Oversee the maintenance and support of legacy data systems, including Hadoop, Diyotta, DataStage.
• Troubleshoot and resolve complex technical issues related to data systems. • Lead the migration/modernization of legacy systems to modern data platforms, ensuring minimal disruption and maximum efficiency.
• Ensure high availability, reliability, and performance of data systems.
• Implement best practices for data architecture, data management and data governance.
• Collaborate with cross functional teams, including data scientists, analysts and business stakeholders to understand data needs and requirements.
• Provide guidance, mentorship, and roadmap to team members for constant upskilling/cross skilling certifications/bridge gaps.
• Foster a culture of collaboration, innovation, and continuous improvement within the team.
• Stay updated with the latest trends and technologies in data engineering.
• Identify opportunities for innovation and improvement in data processed and systems.
• Implement automation and optimization strategies to enhance data processing efficiency.
• Ability to articulate and communicate based on target audience.
• Build strong relationships with vendors and partners to ensure the successful implementation of data solutions.

Technology and Architecture

• Extensive experience with Azure Data Bricks, Azure Synapse, Azure Data Factory and Azure Devops.
• Strong background in maintaining and supporting legacy systems including Hadoop, Diyotta, NiFi and Data Stage.
• Strong knowledge in Hive, HDFS, Kafka, Sqoop and Spark/PySpark.
• Proven experience in designing, architecting Data Modelling and migrating data systems.
• Excellent leadership, management, and mentoring skills.
• Strong project management skills with the ability to manage multiple projects simultaneously.
• Excellent problem-solving skills and the ability to troubleshoot complex technical issues.
• Strong communication and collaboration skills with the ability to work effectively with cross functional teams.
• Last but not the least certifications in relevant technologies.
• Below are the good to have skills.

o Good Knowledge of SQL, IBM DB2, Netezza.

o Experience with cloud platforms other than azure. (eg AWS, GCP)

o Experience in cloud Data platforms like Snowflake.

o Experience with data governance and data security best practices.